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t-sne matlab toolbox  (MathWorks Inc)


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    MathWorks Inc t-sne matlab toolbox
    T Sne Matlab Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/t-sne+toolbox/pm39548325-518-17-18
    Average 90 stars, based on 1 article reviews
    t-sne matlab toolbox - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: A Generalized Zero-Shot Learning Scheme for SSVEP-Based BCI System
    Article Snippet: Then we use the t-SNE toolbox in MATLAB to perform dimensionality reduction to the 240 × 40-dimensional matrix.

    Article Title: Inferring single-trial neural population dynamics using sequential auto-encoders
    Article Snippet: Data were aligned to the time of perturbation for perturbed trials or the mean perturbation time for the given target direction for unperturbed trials (407 ms for downward targets, 487 ms for upward targets). t-SNE mapped using the t-SNE toolbox for MatLab ( https://lvdmaaten.github.io/tsne/ ).

    Article Title: Extracting Neural Oscillation Signatures of Laser-Induced Nociception in Pain-Related Regions in Rats
    Article Snippet: Then the data were sent to t-Distributed Stochastic Neighbor Embedding (t-SNE) toolbox (MatLab implementation downloaded in t-SNE website) to get a 2D representation.



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    Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed Stochastic Neighbor Embedding (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.

    Journal: bioRxiv

    Article Title: Identification Drug Targets for Oxaliplatin-Induced Cardiotoxicity without Affecting Cancer Treatment through Inter Variability Cross-Correlation Analysis (IVCCA)

    doi: 10.1101/2024.02.11.579390

    Figure Lengend Snippet: Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed Stochastic Neighbor Embedding (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.

    Article Snippet: Our implemented t-distributed Stochastic Neighbor Embedding (t-SNE) toolbox that performs t-SNE calculations ( ) uses the results from the correlation matrix and presents the genes based on their correlation values in 3D using a built-in ‘ tsne ’ function implemented in MATLAB.

    Techniques: RNA Sequencing Assay, Expressing, Extraction, Construct, Generated